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BACKGROUND: In 2018, influenza and pneumonia was the eighth leading cause of death in the United States. Since 1950, non-Hispanic blacks (NHBs) have experienced higher rates of mortality than non-Hispanic whites (NHWs). Previous studies have revealed geographic variation in mortality rates by race. The identification of areas with the greatest disparity in influenza and pneumonia mortality may assist policymakers in the allocation of resources, including for the coronavirus disease 2019 pandemic. RESEARCH QUESTION: Does geographic variation in racial disparity in influenza and pneumonia mortality exist? STUDY DESIGN AND METHODS: The Centers for Disease Control and Prevention database for Multiple Cause of Death between 1999 and 2018 for NHB and NHW decedents ≥ 25 years of age with a Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems code for influenza (J09-J11) and pneumonia (J12-J18) was used. Age-adjusted mortality rates (AAMRs) with 95% CIs were computed by race for Health & Human Services (HHS) regions and urbanization in NHBs and NHWs. RESULTS: In 1999 through 2018, there were 540,476 deaths among NHBs and NHWs 25 to 84 years of age. AAMRs were higher in NHBs than NHWs in each age group and in seven of 10 HHS regions. The greatest disparity was in HHS regions 2 (New York and New Jersey) and 9 (Arizona, California, Hawaii, and Nevada). In HHS region 2, NHBs (24.6; 95% CI, 24.1-25.1) were more likely to die than NHWs (15.7; 95% CI, 15.6-15.9). Similarly, in region 9, NHBs (23.2; 95% CI, 22.7-23.8) had higher mortality than NHWs (16.1; 95% CI, 15.9-16.2). Within these regions, disparities were greatest in the core of major metropolitan areas. A very high AAMR in NHBs was noted in large, central metropolitan areas of region 2: 28.2 (95% CI, 27.6-28.9). INTERPRETATION: In 1999 through 2018, the NHB-NHW disparity in AAMRs from influenza and pneumonia was greatest in central metropolitan areas of HHS regions 2 and 9.

Introduction Vaccination helps to prevent influenza infection and reduce associated costs but the influenza vaccination rate in Texas for adults between the ages of 18 to 64 years old is the lowest in the US. Pharmacies and alternative locations have been shown to help increase vaccination rates but many adults still go unvaccinated. Objective This research aims to determine the factors associated with obtaining influenza vaccination at the pharmacy compared to non-pharmacy locations in Texas. Method This study used pooled Texas Behavior Risk Factor Surveillance System datasets (2014 to 2018) for this assessment. The main outcome variable was categorized into pharmacy and non-pharmacy vaccination locations and analyzed using a logistic regression analysis. Further statistical analysis was done using a multinomial logistic regression after re-categorizing the outcome variable into pharmacy, doctor office, and other locations. Result Blacks were 63% (AOR 0.37, C.I. 0.26, 0.50) and Hispanics were 38% (AOR 0.62, C.I. 0.48, 0.80) less likely to receive influenza vaccinations at the pharmacy respectively when compared to Whites. Furthermore, those who did not live in a Metropolitan Statistical Area (MSA) were 33% (AOR 0.67, C.I 0.53, 0.84) less likely to receive influenza vaccinations at the pharmacy compared to those who lived in an MSA. While there was no observed difference in the likelihood of receiving influenza vaccination, the unemployed population were 40% (AOR 1.40, C.I 1.15, 1.71) more likely to be vaccinated in the pharmacy compared to the employed population. Conclusion There is potential for increased utilization of pharmacies as a source of influenza vaccination in Texas. Racial differences exist both for receiving influenza vaccinations and being vaccinated in the pharmacy. Influenza vaccination advocacy and education efforts may be necessary to improve pharmacy-based vaccination in Texas, especially for minorities and rural-dwelling Texans.

Introduction: While improved safety is a highly cited potential benefit of autonomous vehicles (AVs), at the same time a frequently cited concern is the new safety challenges that AVs introduce. The literature lacks a rigorous exploration of the safety perceptions of road users who will interact with AVs, including vulnerable road users. Addressing this gap is essential because the successful integration of AVs into transportation systems hinges on an understanding of how all road users will react to their presence. Methods: A stated preference survey of the Phoenix, Arizona, metropolitan statistical area (Phoenix MSA) was conducted in July 2018. A series of ordered probit models was estimated to analyze the survey responses and identify differences between various population groups with respect to the perceived safety of driving, cycling, and walking near AVs. Results: Greater exposure to and awareness of AVs are not uniformly associated with increases in perceived safety. Various attitudinal factors, level of AV automation, and other intrinsic and extrinsic factors are related to safety perceptions of driving, walking, and cycling near AVs. Socioeconomic and demographic characteristics, such as gender, age, income, employment, and automobile usage and ownership, have various relationships with perceived safety. Conclusions: Cycling near an AV was perceived as the least safe activity, followed by walking and then driving near an AV. Both similarities and differences were observed among the factors associated with the perceived safety of different travel alternatives. Practical Applications: Public perception will guide the development and adoption of AVs directly and indirectly. To help maintain control of public perception, transportation planners, decision makers, and other stakeholders should consider more deliberate and targeted messaging to address the concerns of different road users. In addition, more careful pilot testing and more direct attention to vulnerable road users may help avoid a backlash that could delay the rollout of this technology.

This paper proposes two novel measures to study the geographic mobility of faculty members from their graduating institutions in the United States: a continuous measure using geographic distance and a discrete one concerning the concept of Metropolitan Statistical Area (MSA). The joint application of the two novel measures to a hand-collected hiring network dataset including more than 15,000 faculty members in three disparate disciplines (business, computer science, and history) leads to interesting findings regarding geographic mobility of American professors from graduating institutions, defined by relocation distance or cross-MSA from the PhD granting institution and the hiring institution. Overall, American faculty exhibits high geographic mobility from their graduating institutions in terms of relocation distance and cross-MSA moves. History faculty members have the highest mobility while those in business show the lowest mobility. We further find that assistant professors show the highest mobility while full professors show lowest mobility. In addition, while there is little distance difference between male and female faculty members overall, female faculty members are less likely to move between MSAs or regions in the United States.

Purpose Students with disabilities with unmet health care needs are vulnerable to adverse educational outcomes, including exclusionary discipline. We examined the association between schools' spatial proximity to health care providers and their use of suspension to discipline students with disabilities. Methods The study sample included the 398 public secondary schools in the Boston Metropolitan Statistical Area. We merged census-tract and school-level data from several sources, including the American Community Survey, the Health Resources and Services Administration, the Massachusetts Department of Public Health, and the U.S. Department of Education. Zero-inflated beta regression models were used to examine the association between schools' locations in medically underserved areas (MUAs) and the out-of-school suspension rates of students qualifying for special education services in the 2013–14 school year. Nested models and mediation analysis were used to parse the effects of medical underservice and neighborhood poverty on suspension rates. Results The suspension rate of students with disabilities was about 5 percentage points higher in schools located in medically underserved areas compared to schools that are not in MUAs, controlling for school- and neighborhood-level characteristics (z = 1.97, p Conclusions The findings indicate that schools with limited geographic access to health care services may more likely to use suspension as a tool to manage the behavior of students with disabilities.

Various qualities of transit services, including travel time, frequency, and the presence of alternative paths, affect accessibility—how easily passengers can reach their destinations by transit. Traditional accessibility metrics, such as gravity-type and cumulative-opportunity indices, rely exclusively on travel time as a proxy for travel impedance, failing to consider other qualities of transit services. This study develops a comprehensive transit-based job accessibility index that accounts for the number of feasible alternative routes and their frequency in addition to in-vehicle and out-of-vehicle travel times. It uses the General Transit Feed Specification (GTFS) data and Dijkstra's shortest path algorithm to compute these components of tract-to-tract transit trips in the Chicago Metropolitan Statistical Area (MSA). We demonstrate that conventional accessibility indices considering only gross travel time overestimate job accessibility in the job rich downtown area and suburban train hubs, while they tend to underestimate job accessibility in places mainly served by a suburban bus system. Logistic regression analysis shows that our refined job accessibility measure explains the likelihood of transit commute considerably better than conventional measures.

Using Lorenz-type curves, means tests, ordinary least squares, and locally weighted regressions (LWR), we examine the relative burdens of whites, blacks, and Hispanics in Georgia from road and air traffic noise. We find that whites bear less noise than either blacks or Hispanics and that blacks tend to experience more traffic noise than Hispanics. While every Metropolitan Statistical Area (MSA) showed that blacks experienced relatively more noise than average, such a result did not hold for Hispanics in roughly half of the MSAs. We find much heterogeneity across Census tracts using LWR. For most Census tracts, higher black and Hispanic population shares are associated with increased noise. However, 5.5% of the coefficients for blacks and 18.9% for Hispanics are negative, suggesting larger population shares are associated with less noise. The noise LWR marginal effects for black populations across most tracts in the state are consistent with diminishing marginal noise from additional black population, while those in Atlanta exhibit diminishing marginal noise for Hispanics. In many regions of the state where the potential for health-damaging noise exists, we find relatively high disproportionality in noise experienced by the black and Hispanic populations compared to the rest of the overall population. Our findings underscore the importance of using nonparametric estimation approaches to unveil spatial heterogeneity in applied urban and housing economics analyses.

BACKGROUND Infants younger than 6 months are at increased risk of complications and mortality from pertussis infection. In October 2012, the Advisory Committee on Immunization Practices revised its recommendation to include a Tdap dose during each pregnancy, ideally between 27 and 36 weeks gestation. OBJECTIVE Assess trends in Tdap vaccination coverage among privately insured pregnant women from 2009 to 2016 including timing of Tdap vaccination (before, during, or after pregnancy), trimester of vaccination for women vaccinated during pregnancy, and missed vaccination opportunities for unvaccinated women. Identify factors associated with vaccination during the optimal period of 27-36 weeks gestation. STUDY DESIGN Retrospective analysis of privately insured women 15-49 years who delivered live births during 2009-2016 conducted using 2009-2016 MarketScan data. Tdap vaccination coverage and the timing of Tdap vaccine administration were assessed for women continuously enrolled from 6 months before pregnancy to 1 month after delivery. Multivariable logistic regression was performed to identify factors independently associated with receipt of Tdap vaccine at 27-36 weeks gestation. RESULTS Tdap vaccination coverage during pregnancy increased from 0.4% in 2009 to 6.2% in 2012 and to 53.2% in 2016. The proportion of vaccinated women receiving Tdap at 27-36 weeks gestation increased from

Numerous studies have been conducted to examine the characteristics of urban sprawl at multiple scales, ranging from neighborhood, to city, and metropolitan statistical area. However, few studies have investigated urban sprawl in a megaregion, particularly from a multiple spatial and temporal scale perspective. Focusing on the Beijing-Tianjin-Hebei (BTH) megaregion, one of the largest urban megaregion in China, we quantified the multiscale characteristics of urban sprawl, and how they changed by time, using a combination of density (land consumption per capita) and centrality (Moran’s I coefficient of developed land) indicators. We found: (1) The BTH urban megaregion experienced rapid urban expansion during 1984–2015, with large variations in annual growth rates, and the two measures of sprawl among cities and counties. (2) Land consumption per capita in the megaregion had a clear increasing trend at all three levels, suggesting decreased density and land use efficiency, and thus increased urban sprawl. (3) In contrast, Moran’s I coefficient had trends of increase at multiple scales, suggesting urban developed lands tended to become more clustered spatially. (4) Nonlinear relationships between the two measures of sprawl and the total area and proportional cover of developed lands at county level. Land consumption per capita first increased, and then decreased with the increase of the total area and proportional cover of developed lands, following the pattern of the reversed U shape curve. Similar patterns were found for Moran’s I coefficient. Our results highlight the importance of quantifying urban sprawl at multiple temporal and spatial scales, using multi-dimensional indicators. Results from this study can enhance our understanding on the spatiotemporal characteristics of urban sprawl, and can provide important insights to inform public policy for urban growth management and planning.

We examine the impact of extreme weather events on the cost of an audit. We measure impact as the number of days per year a firm experiences an extreme weather event of any type (e.g., drought, floods, storms, wildfires) in its metropolitan statistical area (MSA). We first find that auditors charge significantly higher fees for firms exposed to more extreme weather days in the past, suggesting that auditors consider previous extreme weather risk exposure a material business risk. No one weather type dominates this finding. Second, auditors charge higher fees for firms experiencing abnormal increases in extreme weather days contemporaneously. This positive relation also strengthens for unanticipated weather events occurring after the fiscal yearend but before the audit report date. Third, we find that extreme weather events generate significantly higher audit fees when the auditor and the client locate in the same MSA.

We introduce evidence from the Covid-19 pandemic in the United States that lends support to future political efforts to include multi-county metropolitan areas as an additional and critical institutional layer&mdash, over and above municipalities, countries, states, or the federal government&mdash, for the effective management of present and future pandemics. Multi-county metropolitan statistical areas (MSAs) accommodated 73% of the U.S. population and, as of 27 September 2020, they were home to 78% of reported cases of Covid-19 and 82% of reported deaths. The rationale for a renewed focus on these spatial units is that they are found to be densely interconnected yet easily identifiable locales for the spread of pandemics and, therefore, for their proper management as well. The paper uses available data on cases and deaths in U.S. counties as of 27 September 2020 to lend statistical support to four hypotheses: (1) The Onset Hypothesis: The onset of Covid-19 cases and deaths commenced earlier in multi-county metropolitan areas than in small-city counties or rural counties, (2) The Peak Hypothesis: The current peak of Covid-19 cases and deaths occurred earlier in multi-county metropolitan areas, (3) The Scaling Hypothesis: Multi-county metropolitan areas had more than their shares of Covid-19 cases and deaths than their shares in the population, and (4) The Neighbor Hypothesis: Levels of Covid-19 cases and deaths in counties within multi-county metropolitan areas were more strongly related to respective levels in their neighboring counties than small-city counties or rural counties. The reported statistical results demonstrate the value of adopting a metropolitan perspective on pandemics and working to empower effective institutional arrangements at the metropolitan level for managing the present and future pandemics.

We use monthly Current Population Survey data to document employment changes during the COVID-19 pandemic at the occupation, industry, and metropolitan statistical area (MSA) levels Over March-April 2020, jobs losses are larger for occupations with higher physical proximity or lower work-from-home feasibility, especially for lower-paying occupations Nonessential industries also see greater declines in employment Such occupational and industrial susceptibility to COVID-19 contributes to the variation in employment changes across MSAs: Employment shrinks more for MSAs with larger pre-crisis fractions of workers employed in occupations with higher infection risk Over April-June 2020, occupations and industries that are hit harder recoup more jobs, but the recovery is only partial Moreover, the gains are concentrated in lower-paying occupations and a few industries Taken together, these abrupt changes in employment following the COVID-19 outbreak are unprecedented and potentially have long-term implications for occupational inequality and regional disparity

Using data from the 2012 Behavioral Risk Factor Surveillance System (BRFSS) and an index of metropolitan urban sprawl, I estimate the effect of sprawl on the use of important preventive care services. Instrumenting for sprawl with the 1947 Highway Construction Plan, my findings suggest that a standard deviation increase in metropolitan statistical area sprawl reduces the probability that individuals have key preventive care services within recommended timing windows. The results also suggest that a standard deviation increase in sprawl leads to increases in the probability of receiving an annual flu vaccine and obesity.

CO-PrIDE was a three-year Pre-Exposure Prophylaxis (PrEP) demonstration project to increase access to PrEP for men who have sex with men and transgender people in the Denver/Aurora Metropolitan Statistical Area. CO-PrIDE implemented a multi-level framework featuring collaboration between health systems and community organizations to link clients to PrEP prescribers and provide support services intended to help clients overcome socioeconomic barriers to PrEP uptake. These services included payment assistance, insurance navigation, and healthcare navigation. CO-PrIDE implemented a participatory mixed-methods evaluation to understand the services associated with PrEP uptake.From January 2016 to December 2018, navigators screened 10,129 clients for PrEP and offered supportive services. The results indicated that clients who received payment assistance were more likely to accept a PrEP prescription (aPR = 3.52, p.0001). Additionally, clients were more likely to receive a PrEP prescription through a co-located health system model, meaning the clinical provider is located with the PrEP Navigator (aPR = 3.78, p.001).The primary factors associated with increased PrEP uptake included co-location of navigation and clinical PrEP services and providing navigation to payment assistance programs. The evaluation results suggest that a multi-level framework that includes diverse support services is needed to implement a sustainable PrEP program.

We value climate amenities by estimating a discrete location choice model for US households. The utility of each metropolitan statistical area (MSA) depends on location-specific amenities, earnings opportunities, housing costs, and the cost of moving to the MSA from the household head’s birthplace. We use the estimated trade-off among wages, housing costs, and climate amenities to value changes in mean winter and summer temperatures. We find that households sort among MSAs as a result of heterogeneous tastes for winter and summer temperatures. Preferences for winter and summer temperatures are negatively correlated: households that prefer milder winters, on average, prefer cooler summers, and households that prefer colder winters prefer warmer summers. Households in the Midwest region, on average, have lower marginal willingness to pay to increase winter and reduce summer temperatures than households in the Pacific and South Atlantic census divisions. We use our results to value changes in winter and summer temperatures for the period 2020 to 2050 under the B1 (climate-friendly) and A2 (more extreme) climate scenarios. On average, households are willing to pay 1 percent of income to avoid the B1 scenario and 2.4 percent of income to avoid the A2 scenario.

Distance to the CBD and neighboring commercial employment (land-use) have been the core determinants of spatial-related production externalities for firms. In these models, travel time to work (firms) is the single most important factor for residential land-use allocation. New theories of complex urban systems (CUS), however, have begun to cast some doubt on the efficacy of the “distance to CBD” model. There is some evidence for example, that large urban systems might evolve with scale-free transportation networks. In this paper, we examine urban land-use data from the Chicago Metropolitan Statistical Area (MSA) to argue for a theoretical shift from a “distance to CBD” based prototype to one that considers the complexity inherent in urban systems structure. We use a Stochastic Greedy Algorithm to quantify connectivity and attractions to every land cell (30 × 30 m) to existing population and employment centers, Points of Interests (POIs), and highway and major roads. We measure the frequency of commercial and resident land-uses relative to these found attraction levels and develop algorithms that help explain the relations. Using these methods, we find that both CBD-driven and network-driven approaches are empirically valid for explaining current urban structures. We also find, however, that these relations change when temporal variables are considered. For example, we found that the land-use change in Chicago from 2001 to 2011 is an obvious deviation from the “distance to CBD” based urban growth assumption. Our results suggest that we should re-examine the core urban structure assumptions of spatial equilibrium models.

This paper proposes ‘agrivoltaic’ system development within Phoenix Metropolitan Statistical Area (MSA) with the objective to generate clean energy in the agricultural lands using solar PV (Photovoltaics) systems thus reducing land commitment and also preserving the agricultural land in the process. Phoenix MSA comprises of two of the fastest growing counties in United States. The study finds that with half density panel distribution, private agricultural lands in the APS (Arizona Public Service) service territory can generate about 8 times the current residential energy demand and 3.4 times the current total energy requirements of the residential, commercial and industrial sectors in the MSA. The Indian Reservation land in the SRP (Salt River Project) service territory has the capacity to generate all of the current residential energy requirement. Most of the agricultural land lies within 1 mile of the 230 and 500 kV transmission lines and is capable of producing 137.5 and 77.5 million MWh of energy. However, with half density panel distribution, an agricultural land received about 60% of direct sunlight compared to a land with no panels. Farmlands have the capacity to generate energy which is significantly more than that required for crop production. Analysis shows that about 50% of the agricultural land sales would have made up for the price of the sale within 2 years with agrivoltaic systems. The effect of preserving the agricultural land and creating a natural growth boundary on urban growth patterns in the rapidly sprawling Phoenix MSA is left as scope for future studies.

Objectives The Centers for Medicare and Medicaid Services plans to institute a 5-year trial of bundled payments for coronary artery bypass grafting through 90 days after discharge. To investigate the impact, we reviewed actual inpatient costs for patients undergoing bypass surgery relative to the target price. Methods A total of 13,276 Medicare patients with estimated cost data underwent isolated coronary artery bypass grafting from 2008 to 2015 in 18 hospitals over 8 Medicare-defined regions within the Commonwealth of Virginia. Actual 2015 inpatient costs were compared with estimated target prices for each year of the pilot, based on the previous 3 years and stratified by Diagnosis-Related Group. Results The mean 2015 cost per patient was $50,394 with high variation (range, $27,862-$74,169). On average, hospitals would receive a refund of $17,682 in year 1, but then owe Medicare increasing amounts up to $367,985 in year 5. If 2015 were the final year of the pilot, 13 of the 18 hospitals (72%) would have owed Medicare for cost overruns averaging $614,270 (range, $67,404-$2,102,292). Costs were below the target price at 5 of 18 hospitals, and the Centers for Medicare and Medicaid Services would have paid them an extra $272,355 on average (range, $88,628-$567,429). Conclusions Hospitals will face immediate financial pressure due to average cost increases of 3.6% per year and an automatic reduction in payment. As regional pricing is phased in, hospitals can expect to owe Medicare increasing amounts. The net effect is shifting of financial risks to hospitals, which could restrict access to care for higher-risk patients.

Chemical transport models (CTMs) are widely used in scientific studies and air quality management. A particular application is to assess how pollutant concentrations, particularly ozone and PM, respond to emission controls. As part of a dynamic evaluation, two widely used CTMs, CMAQ and CAMx, were evaluated for how well they captured trends in observed surface ozone, as well as the changes in associated concentrations, between 2001 to 2011 and 2011 to 2016. Those periods were chosen as additional effort was used to improve emissions estimates for all three years. Prior studies found that both emissions inventories and observations indicate reductions in both ozone and NO2 during these periods, but studies have found that NO2 observations have not agreed as well with estimated emissions. In general, given the efforts to harmonize model inputs, the two models performed very similarly and captured the ozone declines for both the 2001–2011 and 2011–2016 periods at the national level, though moderate biases were found in some locations. At the national scale, ozone trends for the 2011–2016 period were better captured by the models than those for the 2001–2011 period. Both models overestimated the observed decrease in ground level NO2 at the higher end of the concentration spectrum. This is linked to, and can cause, the detected tendency of the models to have larger than observed increases in ozone at the lower end over time. At the metropolitan statistical area (MSA) level, the performance of capturing the ozone trends varied. For some MSA's, the models estimated the wrong direction in the trends; e.g., in Denver, where maximum 8-hr average ozone levels increased from 2001 to 2011, the models predicted a decrease. The US EPA recommends location specific Relative Response Factors (RRFs) to adjust results when applying the models for air quality management purposes. At the regional level, the simulated ozone RRFs were up to 8% larger than the observed RRFs for the 2001–2011 period, suggesting that the models underestimated the ozone decrease. For the 2011–2016 period, with a couple of exceptions, the simulated RRFs were up to 9% smaller than observed RRFs, indicating a negative bias in the simulated trend. For individual MSAs, the ratio of the simulated to observed RRFs ranged between 0.86 (Knoxville for 2001–2011) and 1.40 (Los Angeles for 2001–2011). This is possibly linked to potential biases in the estimated emissions trends. Such high biases could lead to similar biases in the estimated emissions controls required for an area to attain the air quality standards. The results indicate that there are both spatial and temporal biases in how well the two models have captured the observed ozone and NO2 trends. Air quality planning agencies should aim to diagnose and reduce such biases before using model results for air quality management.

Introduction Autonomous Vehicles (AVs) could have profound effects on mobility, safety, and the build environment. In specific, AVs are expected to provide more mobility choices to the elderly and underserved areas, reduce traffic congestion and transportation costs, among others. The changes in built environment could result in a reduction in active travel and physical activity, which might lead to increases in non-communicable diseases (NCD) and pose risks to public health. Methodology Using a combination of available secondary data and the responses of an online survey from adults’ residents of the Chicago metropolitan statistical area, this study aims to enhance the understanding of the individual and location-based characteristics that might influence the levels of adoption of AVs. A market segmentation analysis was first conducted to classify respondents into five distinct AV adoption levels and identify common characteristics. Built environment and health-related characteristics, that surround the ZIP codes where different levels of adopters reside, were also examined using an ordered probit model in order to understand the influence that AV adoption would have on the factors related to active travel. Results The ordered probit estimation results suggest that the level of adoption is associated with a combination of individual and location-based characteristics, some of which are related to active travel behavior. It was found that respondents in the high adopter categories are generally lacking opportunities for active travel and show high levels of NCD in the ZIP codes where they reside. Conclusions AV implementation based only on the propensity to adoption might result in adverse health outcomes. Our results can inform planning strategies and health interventions so as to avoid a massive shift from active travel modes to AVs and mitigate any other adverse impacts on public health that this technology might bring.

Recently shrinkage phenomenon in urban areas has gained broader attention to scholars, policymakers, and practitioners. There has been considerable effort devoted to unveiling various facets of shrinkage within the literature. From a different perspective, this study explicitly concentrates on the influence of the latent effects including space, time, and spatiotemporal interaction on dynamic shrinkage process based upon neighborhood-level (census tract) population shifts in Ohio for the period 1970–2010. To explore those random influences, we hypothesize that the shrinkage of population in census tracts over previous decades is in close association with growth/decline of neighboring tracts (spatial and temporal dependencies). The study adopts a full Bayesian hierarchical analytic framework that specifically utilizes the Conditional Autoregressive (CAR) and Penalized Complexity (PC) priors in order to account for the latent effects on dynamic process. For 635 census tracts in Cleveland-Elyria Metropolitan Statistical Area, Ohio in the U.S., we have found that when the size of initial population of a tract increases, it is more likely to observe population decline on average. Similarly, the relative share of African American population, unemployment rate, and poverty rate has shown a negative correlation with population growth. Our model reveals that there exists a significant influence of the random (latent) effects: a spatial correlation from adjacent tracts, a non-linear temporal dependence, and a spatiotemporal interaction complementing the random fluctuation. Moreover, we present areas of higher risks that are census tracts with higher probabilities (close to 1) of losing 10% or more of their relative population. We believe that the findings of our study allow us to support informed decision making for devising policies of shrinking regions.

Transportation networks and related urban form settlements are frequently recognized as barriers to primary care access. This study explores the role of urban form in constraining accessibility to healthcare as affected by transportation network characteristics. The aim of the study is to measure the spatial accessibility to primary health care providers while controlling for the impact of built environment factors. Orlando Metropolitan statistical area, in Florida, USA, is used as a case study. This study develops a multi-dimensional approach to measure urban form components – density, mixed use, street network and proximity - and spatial measures of accessibility to primary care providers by employing Geographic Information Systems (GIS) technology. Ordinary Least Square (OLS) regression is used to assess the impact of urban form characteristics to primary health care providers’ accessibility, and to verify previous research that concludes that places with more sprawl have less accessibility to health care facilities. Considering both nurse practitioners (NPs) and primary care physicians (PCPs) as primary health care providers, about 85.67% of total population of Orlando Metropolitan Statistical Area (MSA) has access to the nearest provider in less than 5 minute drive, which represents remarkable levels of accessibility. In the regression results, the density component shows a positive and proximity a negative and significant correlation to all primary care accessibility measures; whereas the mixed-use components show both positive and negative correlation. The findings from this study show that a more nuanced relationships exists between urban form components and accessibility of primary health care.

Purpose To assess cross-population linkages in HIV/AIDS epidemics, we tested the hypothesis that the number of newly diagnosed AIDS cases among Black people who inject drugs (PWID) was positively related to the natural log of the rate of newly diagnosed HIV infections among Black non-PWID heterosexuals in 84 large U.S. metropolitan statistical areas (MSAs) in 2008–2016. Methods We estimated a multilevel model centering the time-varying continuous exposures at baseline between the independent (Black PWID AIDS rates) and dependent (HIV diagnoses rate among Black heterosexuals) variables. Results At MSA level, baseline (standardized β = 0.12) Black PWID AIDS rates and change in these rates over time (standardized β = 0.11) were positively associated with the log of new HIV diagnoses rates among Black heterosexuals. Thus, MSAs with Black PWID AIDS rates that were 1 standard deviation= higher at baseline also had rates of newly diagnosed HIV infections among Black non-PWID heterosexuals that were 10.3% higher. A 1 standard deviation increase in independent variable over time corresponded to a 7.8% increase in dependent variable. Conclusions Black PWID AIDS rates may predict HIV rates among non-PWID Black heterosexuals. Effective HIV programming may be predicated, in part, on addressing intertwining of HIV epidemics across populations.

This study examines whether being located within a 100-year floodplain has an impact on the price of residential single-family house sales using house sales data in the Fargo-Moorhead Metropolitan Statistical Area between 2000 and 2013. A spatial quantile regression is applied to investigate the flood hazards impact on conditional higher- vs lower- priced homes, while accounting for spatial autocorrelation. The findings show that the location within a floodplain reduces property value. Furthermore, the negative impact of flood hazards on property values are stronger among lower-priced homes, and weaker among higher-priced homes. In addition, the study examines if a major flood in 2009 had an impact on the home buyers' perception about flood risk. The results show that about a year after the major flood, home buyers responded the most, however, the effect quickly diminished after 2010. Across quantiles, the 2009 flood had more effect on lower-priced than higher-priced homes.

We construct monthly economic activity indices for the 50 largest U.S. metropolitan statistical areas (MSAs) beginning in 1990. Each index is derived from a dynamic factor model based on twelve underlying variables capturing various aspects of metro area economic activity. To accommodate mixed-frequency data and differences in data-publication lags, we estimate the dynamic factor model using a maximum-likelihood approach that allows for arbitrary patterns of missing data. Our indices highlight important similarities and differences in business cycles across MSAs. While a number of MSAs experience sizable recessions during the national recessions of the early 1990s and early 2000s, other MSAs escape recessions altogether during one or both of these periods. Nearly all MSAs suffer relatively deep recessions near the recent Great Recession, but we still find significant differences in the depth of recent metro recessions. We relate the severity of metro recessions to a variety of MSA characteristics and find that MSAs with less-educated populations and less elastic housing supplies experience significantly more severe recessions. After controlling for national economic activity, we also find significant evidence of dynamic spillover effects in economic activity across MSAs.

The paper examines the relationship between climate amenities and locational choices in retirement. Using data from 2017 release of the American Community Survey, I construct a household residential location choice model and value climate amenities from the trade-offs among housing cost, climate amenities, and other locational attributes in a metropolitan statistical area (MSA). On average, a retired household is willing to pay $1209 for a 1 °C drop in average summer temperature, $1114 for a 1 °C increase in average winter temperature, and $486 for a 1 °C decrease in temperature variability. The values of climate amenities vary with household demographic characteristics, and older households with a higher retirement income and disability have a higher marginal willingness to pay for a favorable climate. Moreover, among the retired population, there exists a positive preference-based sorting across MSAs, where those favoring the preferred temperatures more than the average live in places with a more friendly climate. Using the estimated preference parameters, I compute the values of projected climate amenities and find that retired households would be willing to pay nearly 3.3% of their annual income to avoid a standard future projected climate scenario. Simulation results suggest that over 2% of retired households would relocate in response to this level of climate change, resulting in an overall northbound shift in the retired population.

In August 2017, Hurricane Harvey struck the Texas Gulf Coast, causing record flooding in the Houston Metropolitan Statistical Area (“Greater Houston”). Our study assesses unmet needs and adverse event experiences of Greater Houstonians during and after Harvey using a suite of indicators of social vulnerability and disaster impacts. Indicators of social vulnerability have not been well integrated within US post-disaster needs assessment protocols. Using data collected within four months of Hurricane Harvey via a structured survey that was representative of the Greater Houston population, we employed bivariate and multivariable analyses to assess differences in unmet needs and adverse event experiences based on social vulnerability characteristics. Within the Hispanic population, we observed bivariate differences based on nativity (US-born vs. foreign-born) and US citizenship status. Foreign-born Hispanic people without US citizenship were more likely to suffer from particular unmet needs and adverse event experiences compared to Hispanic US citizens. Multivariable models revealed that racial/ethnic minority and lower-income households experienced significantly more unmet needs than non-Hispanic White and higher-income households during and after Harvey. Foreign born Hispanics who were citizens experienced significantly more adverse event experiences than non-Hispanic whites. The fact that socially vulnerable subgroups experienced disparate unmet needs following Harvey indicates that improvements in US post-disaster needs assessment protocols are imperative. Needs assessments should integrate a focus on social vulnerability, so that disaster assistance may be targeted to better meet survivors’ needs.

In this paper we investigate the effects of tornado activity on house prices and stock returns in the US. First, using geo-referenced and metropolitan statistical area (MSA)-level data, we find tornado activity to be responsible for a significant drop in house prices. Spillover tornado effects between adjacent MSAs are also detected. Furthermore, our granular analysis provides evidence of tornadoes having a negative impact on stock returns. However, only two sectors seem to contribute to such a negative effect (i.e., consumer discretionary and telecommunications). In a macro-analysis, which relies on aggregate data for the South, West, Midwest and Northeast US regions, we then show that tornado activity generates a significant drop in house prices only in the South and Midwest. In these regions, tornadoes are also responsible for a drop in income. Tornado activity is finally found to positively (negatively) affect stock returns in the Midwest (South). If different sectors are examined, a more heterogeneous picture emerges.

Auditing standards require auditors to evaluate the reasonableness of reported fair value estimates, but audit regulators frequently cite auditors for deficiencies in these estimates. Specific to goodwill, auditors must evaluate the probability that recorded goodwill is impaired. Based on small sample frames and availability theories, we predict that experiencing a recorded impairment at an unrelated client increases auditors’ internal perceived probability of downside risk. As a result, we expect more impairments at subsequent clients with economic indicators of impairment. Using a sample of 7,500 client-years from 2004-2014 with potential goodwill impairments, we find evidence consistent with our expectation at the audit office level. We also find evidence at the metropolitan statistical area and non-Big 4 audit firm levels; however, consistent with our expectation that the closer the auditor is to the prior impairment the stronger the effect, the audit office level effect is stronger than the other two levels and is especially strong in audit offices below the median size. Our study suggests that enhancing knowledge sharing around experienced goodwill impairments could help improve auditor difficulties in auditing uncertain fair value estimates and increase recognition of goodwill impairments.

Rising economic segregation suggests a need to examine constraints to job access by race/ethnicity and economic inequality simultaneously. This often requires detailed socio-spatial interaction data to make progress on theoretical and modeling development, empirical studies and policy insights. Commuting data are commonly used because of its wide availability. Despite excellent work trip datasets from the U.S. Census such as the Census Transportation Planning Package and the Longitudinal Employer-Household Dynamics (LEHD) data, there are often gaps between the data that are available and ideal detailed commuting data suited to models and data analysis. This is because commuting data are available for a limited set of socio-economic dimensions and this coarseness limits researchers in their ability to uncover nuances of place-based generalizations about commuting, either socially or spatially. In one promising approach, an information minimizing technique was proposed as a workable practical method to synthesize disaggregated work trip flows. Because the strength of fit between predicted and observed trips is unknown, this paper validates this method using real commutes disaggregated by income and then synthesizes race–income work trips using LEHD data for the Wichita, Kansas metropolitan statistical area. We find that low-income Whites travel longer distances and have more dispersed travel patterns than all African-American and Asian income groups and that both low- and middle-income groups of all race groups have spatially constrained flows.

Location-based social media provide an enormous stream of data about humans' life and behavior. With geospatial methods, those data can offer rich insights into public health. In this research, we study the effect of climate and seasonality on the prevalence of depression in Twitter users in the U.S. Text mining and geospatial methods are used to detect tweets related to depression and their spatiotemporal patterns at the scale of Metropolitan Statistical Area. We find the relationship between depression rates, climate risk factors and seasonality are varied and geographically localized. The same climate measure may have opposite association with depression rates at different places. Relative humidity, temperature, sea level pressure, precipitation, snowfall, weed speed, globe solar radiation, and length of day all contribute to the geographic variations of depression rates. A conceptual compact map is designed to visualize scattered geographic phenomena in a large area. We also propose a three-stage framework that semi-automatically detects and analyzes geographically distributed health issues using location-based social media data.

The scope of empirical environmental justice (EJ) research has expanded beyond hazards exposure to scrutinize social inequities in access to amenities, but no prior study has examined the EJ implications of public beach access. Furthermore, quantitative research on white privilege is very scarce. To address these knowledge gaps, our study examines racial/ethnic and socioeconomic inequities in access to public beaches in the Miami metropolitan statistical area, Florida. Public beach accessibility is modeled with an innovative geospatial approach that involves population weighted distances to beach access sites. To assess EJ implications of public beach access for various racial/ethnic and socioeconomically vulnerable groups, spatial regression models are estimated using census tract-level data. Results indicate that beaches are more accessible to neighborhoods with a higher proportion of non-Hispanic Whites, while neighborhoods with higher percentages of Hispanics and socioeconomically disadvantaged residents have limited access. This study demonstrates the importance of assessing white privilege and access to environmental amenities in EJ research to better understand social inequities.

In this study, we explored the spatial and temporal patterns of land cover and land use (LCLU) and population change dynamics in the St. Louis Metropolitan Statistical Area. The goal of this paper was to quantify the drivers of LCLU using long-term Landsat data from 1972 to 2010. First, we produced LCLU maps by using Landsat images from 1972, 1982, 1990, 2000, and 2010. Next, tract level population data of 1970, 1980, 1990, 2000, and 2010 were converted to 1-km square grid cells. Then, the LCLU maps were integrated with basic grid cell data to represent the proportion of each land cover category within a grid cell area. Finally, the proportional land cover maps and population census data were combined to investigate the relationship between land cover and population change based on grid cells using Pearson's correlation coefficient, ordinary least square (OLS), and local level geographically weighted regression (GWR). Land cover changes in terms of the percentage of area affected and rates of change were compared with population census data with a focus on the analysis of the spatial-temporal dynamics of urban growth patterns. The correlation coefficients of land cover categories and population changes were calculated for two decadal intervals between 1970 and 2010. Our results showed a causal relationship between LCLU changes and population dynamics over the last 40 years. Urban sprawl was positively correlated with population change. However, the relationship was not linear over space and time. Spatial heterogeneity and variations in the relationship demonstrate that urban sprawl was positively correlated with population changes in suburban area and negatively correlated in urban core and inner suburban area of the St. Louis Metropolitan Statistical Area. These results suggest that the imagery reflects processes of urban growth, inner-city decline, population migration, and social spatial inequality. The implications provide guidance for sustainable urban planning and development. We also demonstrate that grid cells allow robust synthesis of remote sensing and socioeconomic data to advance our knowledge of urban growth dynamics from both spatial and temporal scales and its association with population change.

I estimate the effects of U.S. Metropolitan Statistical Area (MSA) housing prices on a variety of health outcomes and risky health behaviors separately for homeowners and tenants. The constructed dataset consists of information on individuals from the 2002-2012 Behavioral Risk Factor Surveillance System (BRFSS) combined with homeownership data from the March Current Population Survey (CPS) and housing prices from Freddie Mac. I estimate positive results for homeowners in terms of their health and negative results for tenants. I also find increases in risky behaviors among tenants associated with increases in housing prices, which may be driving the reduction in their health status. Those estimated effects are concentrated on low income homeowners and tenants. The estimated contemporaneous effects do not persist in the long run while the effects of an increase in housing prices on being obese become more pronounced for homeowners, resulting in worse self-reported health.

This paper examines how the Securities and Exchange Commission’s (SEC) enforcement actions and whom they target deter future financial misconduct. An enforcement action reduces the incidence of misconduct in other firms in the same industry and metropolitan statistical area (MSA) in the future. Furthermore, an enforcement that punishes a guilty company has a larger deterrence effect on future misconduct than punishing an officer, auditor, attorney, or other entity. In addition, the results are robust to using alternative measures of financial misconduct such as restatements and Fscore. These results have several policy implications on how regulatory agencies can maximize the value of their enforcements.

We study whether foreign banks increased or decreased lending in the United States during the 1990-1991, 2001, and 2007-2009 recessions. Using a matched sample of foreign banks paired with domestic banks, univariate tests show that commercial and industrial loans by foreign banks increased in the 1990-1991 recession, decreased in the 2001 recession, and marginally increased in the 2007-2009 recession. Since recessions have differential impacts in an economy, we tested the lending behavior using granular data at the local metropolitan statistical area (MSA) level. Multivariate test results show that foreign branches engaged in countercyclical lending in the 1990 and 2001 recessions and foreign subsidiaries in the 2008 recession by lending in MSAs where GDP was falling or unemployment increasing. We conclude foreign banks continue to play a positive role in the American economy.

Within the social sciences, there is a long and storied history of the effect of economic conditions on vote choice. The traditional arguments are that voters have personal (egotropic) and/or other-regarding (sociotropic) preferences and that they reward and punish politicians electorally based on economic conditions at these levels. However, there is a third option. As industries, employment, and economic conditions are not uniformly distributed across the country, preferences may be locally based. This project combines unique survey data with Metropolitan Statistical Area unemployment numbers and finds evidence of distinct preferences at a third “communotropic” level.

The American Heart Association/American Stroke Association guidelines recommend all patients presenting to emergency departments (EDs) with a potential stroke be seen within 10 minutes of arrival, although this may not be achieved in all patients. We sought to identify factors associated with delayed evaluation of ED patients with potential stroke.Using the National Hospital Ambulatory Medical Care Survey, we identified all patient ED visits from 2003 to 2010 and further identified those patients with strokes or stroke-like symptoms using International Classification of Disease, Ninth Revision codes. Visits were classified as those evaluated within 10 minutes of ED arrival or those where evaluation by the treating provider was 10 minutes or greater (delayed evaluation). We stratified visits, compared proportions, and calculated the unadjusted and adjusted odds ratios (ORs) in a multivariable model.We identified 743 cases in the database representing an estimated 2.3 million ED visits for patients with strokes. Of these, 600000 were seen within 10 minutes and 1.7 million visits with delayed evaluation. Visits at nonmetropolitan statistical area hospitals were associated with decreased odds of delayed evaluation (OR, 0.41 [95% confidence interval, 0.26-0.64]; P.001). Being triaged to a less urgent emergency severity index category was associated with increased odds of delayed evaluation (OR 3.08 (95% CI 1.94-4.89) p0.001). Other factors were not associated with delayed evaluation.In this national sample of patients presenting with strokes to US EDs, patient visits to metropolitan statistical area hospitals and those triaged to less urgent categories were associated with delayed evaluation.

Objective To examine preventive care visit patterns among commercially insured adolescents during 2003-2010. In 2005-2007, the Advisory Committee on Immunization Practices (ACIP) recommended 3 vaccines targeted at adolescents. We also investigate the relationship between preventive care visits and immunization. Study design Data were drawn from the MarketScan database. Adolescents aged 11-21 continuously enrolled in the same insurance plan during the calendar year were included. We calculated the annual proportion of adolescents with at least 1 preventive and 1 vaccination-related visit. Longitudinal analyses were conducted by following the 1992 birth cohort for 8 consecutive years. Results The proportion of adolescents making at least 1 preventive visit increased from 24.6%-41.1% during 2003-2010. The rate of vaccination-related visits increased from 12.9%-26.3%. The magnitude of the increase in preventive and vaccination-related visits was greater during the years in which ACIP issued recommendations. The rates of preventive and vaccination-related visits were considerably higher among female and early adolescents and adolescents in managed care plans. Longitudinal analyses indicated that only 2.4% of adolescents had an annual preventive visit during the 8 years. Conclusions Yearly improvements in preventive care visits by adolescents were substantial. ACIP recommendations may be associated with this improvement. However, ongoing efforts are needed to improve the use and delivery of preventive care services.

A long stream of academic literature has established that public funding towards research and development matters for economic growth because it relates to increases in innovation, productivity and the like. The impact of public funding on the creation of new firms has received less attention in this literature despite theoretical constructs that support such association. In the present paper we study whether indeed there is a relationship between public research funds and local firm births in the context of the U.S. biotechnology industry. In doing so, we introduce a number of changes that strengthen the robustness of our findings when compared with existing literature. These changes include a direct measure of research expenditures and a considerably lengthier longitudinal dataset which allows us to capture a structural relationship and not a chance event. We empirically demonstrate that increases in the level of research funding from the National Institutes of Health towards biotechnology associate with increases in the number of biotechnology firm births at the Metropolitan Statistical Area level. Further, we reveal that public funds towards established firms associate with local firm births considerably more strongly when compared with funds towards universities and research institutes/hospitals. We conclude the paper with academic and policy implications of the present work that highlight the complexity of factors that underlie the creation of local firms in high technology industries.\ud \ud

This study examined the association between ozone and fine particulate (PM2.5) exposure and asthma risk by place of residence. We linked 412,832 adult respondents from the 2009 U.S. Behavioral Risk Factor Surveillance System to their residence counties. Observed and interpolated ozone and PM2.5 concentration data from 2006 to 2009 were used as exposures. We linked self-reported current asthma status and other individual risk factors to county-level risk factors in multilevel logistic regressions. Results indicated spatially varied asthma risks and spatially varied associations between ambient air pollution and asthma risk. Residents in counties not located within a metropolitan statistical area (MSA) and in inner ring suburbs had a relatively higher asthma risk. Positive ozone-asthma associations were detected across all spatial settings, while positive PM2.5-asthma associations were detected only in central cities of an MSA and in outer ring suburbs, indicating that residence location modified the relationship between ambient air pollution and asthma risk.

Some cancer survivors report spending 20% of their annual income on medical care. Undue financial burden that patients face related to the cost of care is referred to as financial hardship, which may be more prevalent among rural cancer survivors. This study examined contrasts in financial hardship among 1419 rural and urban cancer survivors using the 2011 Medical Expenditure Panel Survey supplement - The Effects of Cancer and Its Treatment on Finances. We combined four questions, creating a measure of material financial hardship, and examined one question on financial worry. We conducted multivariable logistic regression analyses, which produced odds ratios (OR) for factors associated with financial hardship and worry, and then generated average adjusted predicted probabilities. We focused on rural and urban differences classified by metropolitan statistical area (MSA) designation, controlling for age, education, race, marital status, health insurance, family income, and time since last cancer treatment. More rural cancer survivors reported financial hardship than urban survivors (23.9% versus 17.1%). However, our adjusted models revealed no significant impact of survivors' MSA designation on financial hardship or worry. Average adjusted predicted probabilities of financial hardship were 18.6% for urban survivors (Confidence Interval [CI]: 11.9%-27.5%) and 24.2% for rural survivors (CI: 15.0%-36.2%). For financial worry, average adjusted predicted probabilities were 19.9% for urban survivors (CI: 12.0%-31.0%) and 18.8% for rural survivors (CI: 12.1%-28.0%). Improving patient-provider communication through decision aids and/or patient navigators may be helpful to reduce financial hardship and worry regardless of rural-urban status.

The first author acknowledges the support from the National Natural Science Foundation of China under Grant No. 71774152, 91546109; and the Youth Innovation Promotion Association of the Chinese Academy of Sciences (Grant No. Y7x0231505).

Objective To develop a reliable food store observational data collection instrument to be used for measuring product availability, pricing, and promotion. Design Observational data collection. Setting A total of 120 food stores (26 supermarkets, 34 grocery stores, 54 gas/convenience stores, and 6 mass merchandise stores) in the Chicago metropolitan statistical area. Main Outcome Measures Inter-rater reliability for product availability, pricing, and promotion measures on a food store observational data collection instrument. Analysis Cohen's kappa coefficient and proportion of overall agreement for dichotomous variables and intra-class correlation coefficient for continuous variables. Results Inter-rater reliability, as measured by average kappa coefficient, was 0.84 for food and beverage product availability measures, 0.80 for interior store characteristics, and 0.70 for exterior store characteristics. For continuous measures, average intra-class correlation coefficient was 0.82 for product pricing measures; 0.90 for counts of fresh, frozen, and canned fruit and vegetable options; and 0.85 for counts of advertisements on the store exterior and property. Conclusions and Implications The vast majority of measures demonstrated substantial or almost perfect agreement. Although some items may require revision, results suggest that the instrument may be used to reliably measure the food store environment.

This article examines the substantial housing stock declines between 2000 and 2010 in many major US central cities. It updates an analysis first formulated in the 1970s, of an S-shaped housing supply curve, to explain decreases in absolute housing stocks. Explanatory variables include Metropolitan Statistical Area standardized rents, center city prior occupancy rates, regional unemployment rates, and a set of regional and state dummy variables. The analysis provides strong evidence of a lower tail of the S, and more tentative evidence of an upper tail. Market fundamentals explain a considerable portion of the large housing stock losses, but in several cities loss of dwelling units and housing abandonment were worse than could be explained by the fundamentals.

This study contributes to the literature on applied urban geography by examining spatial patterns and processes of changing racial/ethnic diversity within the intra-urban context of Knoxville metropolitan statistical area. Knoxville embraces a diverse economic set up with opportunities in high-tech research and development, manufacturing, tertiary/service-sectors, construction, as well as entertainment industry. This serves well for its continued population growth, including minorities during 1990–2009. This paper explores how the neighborhood-level socioeconomic, demographic, and built-environment characteristics relate to tract-level racial/ethnic diversity, measured by multi-group diversity score and its components. Tools such as isarithmic surface density maps, correlations, principal components and regression analyses are used to examine processes of change. Results indicate that diversity in 1990 associates with negative change whereas diversity in 2000 associates with positive change. Though overall diversity sprawls and increases during 1990–2009, diversity among non-White declines during 2000–2009 and shows spatial confinement. Regressions suggest complicated mosaics of changing neighborhoods, providing evidence of invasion-succession, filtering and resurgence of ethnic-enclaves in specific neighborhoods. Concerning the six counties of the MSA, Knox is the most diverse whereas Union the least, though the share of Hispanics tops in Loudon and Asians in Knox. In terms of strategic planning, findings from this research can be used in creating equitable and sustainable urban communities that can improve the overall well-being of people by reducing racial/ethnic and socio-economic disparities that might occur as undesirable consequences of fast increasing diversity.

Background There is disparity in access to outpatient care for Medicaid beneficiaries. This inequity disproportionately impacts children. Access for children with skin disease may be especially limited. Objective We sought to compare access to dermatologists for new pediatric patients insured by Medicaid versus a private plan. Methods We surveyed 13 metropolitan markets by conducting secret-shopper scripted telephone calls to dermatology providers listed by Medicaid health plans. Paired calls, differing by insurance type, were made to each office on the same day, portraying a parent requesting a new appointment for a child with eczema. Results We called the offices of 723 Medicaid-listed providers. Final analysis included 471 dermatologists practicing general dermatology. Of these, an average of 44% refused a new Medicaid-insured pediatric patient. The average wait time for an appointment did not significantly vary between insurance types. Assuming that dermatologists not listed as Medicaid providers do not see Medicaid-insured children, our data indicate that pediatric Medicaid acceptance rates ranged from 6% to 64% by market, with an overall market size-weighted average acceptance rate of 19%. Relative reimbursement levels for Medicaid-insured patients did not correlate with acceptance rates. Limitations Although the most current health plan directories were used to create calling lists, these are dynamic. The sample sizes of confirmed appointments were in part limited by a lack of referral letters and/or health plan identification numbers. Only confirmed appointments were used to calculate average wait times. Conclusions Access to dermatologists is limited for Medicaid-insured children with eczema.

We investigate the association between geographic spillovers and corporate investment and accruals decisions. We hypothesize that if geographic areas differ by the degree of information sharing among local people, then the quality of managerial decisions can be affected by higher information flow in high-spillover areas. We construct a measure of geographic spillover intensity based on distances among firms in a metropolitan statistical area and test whether geographic spillovers are related to (1) the similarity and (2) the quality of corporate decisions. The findings indicate that in high-spillover areas, managers’ investment and accruals decisions are more similar and have better quality than in low-spillover areas. Our findings contribute to a growing literature on the role of geographic information flow and its effect on corporate outcomes.

We value climate amenities by estimating a discrete location choice model for US households. The utility of each metropolitan statistical area (MSA) depends on location-specific amenities, earnings opportunities, housing costs, and the cost of moving to the MSA from the household head’s birthplace. We use the estimated trade-off among wages, housing costs, and climate amenities to value changes in mean winter and summer temperatures. We find that households sort among MSAs as a result of heterogeneous tastes for winter and summer temperatures. Preferences for winter and summer temperatures are negatively correlated: households that prefer milder winters, on average, prefer cooler summers, and households that prefer colder winters prefer warmer summers. Households in the Midwest region, on average, have lower marginal willingness to pay to increase winter and reduce summer temperatures than households in the Pacific and South Atlantic census divisions. We use our results to value changes in winter and summer temperatures for the period 2020 to 2050 under the B1 (climate-friendly) and A2 (more extreme) climate scenarios. On average, households are willing to pay 1 percent of income to avoid the B1 scenario and 2.4 percent of income to avoid the A2 scenario.

Empirical evidence exists to suggest that sprawl contributes to higher household expenditures on transportation. However, little is known about how sprawl affects the cost of the most recurrent daily trip--the trip to work. To explore the sprawl-work trip relationship, the study adopts a multilevel approach to private-vehicle commuting costs. The multilevel model attempts to determine which measure(s) of sprawl contribute(s) most to higher private-vehicle commuting costs at the household-level after controlling for congestion and average household expenditures on housing and transportation at the Metropolitan Statistical Area- (MSA-) level of analysis. Results show that one measure of sprawl--street accessibility--has a statistically significant though minimal effect on private-vehicle commuting costs and that such costs are higher in MSAs with more congestion and higher average household expenditures on public transportation. Overall, a multilevel approach suggests that congestion contributes more to higher private-vehicle commuting costs than sprawl.